add an unittest

python/paddle/fluid/layers/io.py

@@ -21,7 +21,8 @@ from ..executor import global_scope
 
 __all__ = [
     'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'open_recordio_file',
-    'read_file', 'create_shuffle_reader', 'create_double_buffer_reader'
+    'read_file', 'create_shuffle_reader', 'create_double_buffer_reader',
+    'create_multi_pass_reader'
 ]
 
 

python/paddle/fluid/tests/unittests/test_multi_pass_reader.py

+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import paddle.fluid as fluid
+import paddle.v2 as paddle
+import paddle.v2.dataset.mnist as mnist
+
+
+class TestMultipleReader(unittest.TestCase):
+    def setUp(self):
+        self.batch_size = 64
+        self.pass_num = 3
+        # Convert mnist to recordio file
+        with fluid.program_guard(fluid.Program(), fluid.Program()):
+            data_file = paddle.batch(mnist.train(), batch_size=self.batch_size)
+            feeder = fluid.DataFeeder(
+                feed_list=[
+                    fluid.layers.data(
+                        name='image', shape=[784]),
+                    fluid.layers.data(
+                        name='label', shape=[1], dtype='int64'),
+                ],
+                place=fluid.CPUPlace())
+            self.num_batch = fluid.recordio_writer.convert_reader_to_recordio_file(
+                './mnist.recordio', data_file, feeder)
+
+    def test_main(self):
+        with fluid.program_guard(fluid.Program(), fluid.Program()):
+            data_file = fluid.layers.open_recordio_file(
+                filename='./mnist.recordio',
+                shapes=[(-1, 784), (-1, 1)],
+                lod_levels=[0, 0],
+                dtypes=['float32', 'int64'])
+            data_file = fluid.layers.create_multi_pass_reader(
+                reader=data_file, pass_num=self.pass_num)
+            img, label = fluid.layers.read_file(data_file)
+
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            else:
+                place = fluid.CPUPlace()
+
+            exe = fluid.Executor(place)
+            exe.run(fluid.default_startup_program())
+
+            batch_count = 0
+            while not data_file.eof():
+                img_val, = exe.run(fetch_list=[img])
+                batch_count += 1
+                self.assertLessEqual(img_val.shape[0], self.batch_size)
+                print(batch_count)
+            data_file.reset()
+            self.assertEqual(batch_count, self.num_batch * self.pass_num)